Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
3d object recognition using invariant feature indexing of interpretation tables
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Original Contribution: Stacked generalization
Neural Networks
Symbolic visual learning
MULTI-HASH: learning object attributes and hash tables for fast 3-D object recognition
Symbolic visual learning
Scene Understanding by Rule Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Logical Definitions from Relations
Machine Learning
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We consider a parallel, rule-based approach for learning and recognition of pattern and objects in scenes. Classification rules for pattern fragments are learned with objects presented in isolation and are based on unary features of pattern parts and binary features of part relations. These rules are then applied to scenes composed of multiple objects. We present an approach that solves, at the same time, evidence combination and consistency analysis of multiple rule instantiations. Finally, we introduce an extension of our approach to the learning of dynamic patterns.